(235d) Gene Expression Analysis of Taxus Cell Culture Subpopulations for Targeted Metabolic Engineering of Secondary Metabolite Accumulation | AIChE

(235d) Gene Expression Analysis of Taxus Cell Culture Subpopulations for Targeted Metabolic Engineering of Secondary Metabolite Accumulation

Authors 

Patil, R. A. - Presenter, University of Massachusetts Amherst


Plant cell culture provides an environmentally friendly, renewable alternative for supply of plant derived pharmaceuticals. A notable example of the success of plant cell culture technology is the production of the anti-cancer agent paclitaxel (Taxol?). Our laboratory focuses on development and optimization of bio-processes for production of paclitaxel in Taxus cell suspension cultures, with an emphasis on understanding paclitaxel metabolism at both the molecular and cellular level. One defining characteristic of plant cell suspension cultures is the tendency of cells to grow in aggregates, which introduces significant cell-cell heterogeneity and can affect secondary metabolite accumulation. To both elucidate the relationship between cell aggregate formation and paclitaxel accumulation in Taxus cell culture and to determine more effective strategies for metabolic engineering of specific paclitaxel-accumulating cells, we examined expression of paclitaxel biosynthetic pathway genes in both aggregates of different sizes and accumulating and nonpaclitaxel-accumulating populations. High performance liquid chromatography (HPLC) was used to quantify paclitaxel and related taxanes at the culture level, and quantitative PCR (q-PCR) was used to analyze gene expression in both different aggregate size fractions and subpopulations sorted using fluorescence-activated cell sorting (FACS). Examining expression profiles in both different size aggregates and sorted populations has provided further insight into gene expression profiles associated with a paclitaxel-accumulating state. These analyses have enhanced our understanding of paclitaxel metabolism at the molecular level and have provided a basis for more targeted metabolic engineering and bio-process design.